Vehicle surroundings monitoring device and vehicle surroundings monitoring method

Abstract

To provide a vehicle periphery monitoring device for easily detecting an obstacle in the periphery of a vehicle by using distance sensors.SOLUTION: A vehicle periphery monitoring device 200 includes an obstacle detection section 201 for detecting an obstacle Ob in the periphery of a vehicle 5 based on a difference between respective envelopes W1, W2 of a plurality of reflection waves R1, R2 with respect to a road in the periphery of the vehicle 5, which are obtained by a plurality of distance sensors (e.g., distance sensors 11, 12) mounted on the vehicle 5.SELECTED DRAWING: Figure 8

Description

[Technical Field]

[0001] The present disclosure relates to a vehicle periphery monitoring device that monitors the periphery of a vehicle, and a vehicle periphery monitoring method. [Background technology]

[0002] In order to improve vehicle safety and prevent accidents, the development and introduction of ADAS (Advanced Driving Assistant Systems), which acquire information about the vehicle's surroundings and assist the driver, is accelerating.

[0003] Examples of devices for acquiring information about the surroundings of a vehicle include distance sensors such as ultrasonic sensors and imaging devices such as cameras. Patent Document 1 discloses a vehicle surroundings monitoring device that uses ultrasonic sensors and cameras to detect obstacles such as road gutters. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2016-192035 Summary of the Invention [Problem to be solved by the invention]

[0005] For example, when detecting obstacles using a camera, there is a problem that the detection accuracy around the vehicle decreases in darkness, such as at night. To solve this problem, Patent Document 1 proposes a method using an infrared camera, but infrared cameras are more expensive than regular cameras, and also require the vehicle to be equipped with a new imaging device, which increases the number of parts.

[0006] The present disclosure aims to provide a vehicle surroundings monitoring device and the like that can easily detect obstacles around a vehicle using a distance sensor. [Means for solving the problem]

[0007] A vehicle periphery monitoring device according to one aspect of the present disclosure includes an obstacle detection unit that detects an obstacle around a vehicle based on differences in envelopes of a plurality of reflected waves from a road around the vehicle, the differences being obtained by a plurality of distance sensors mounted on the vehicle. The envelope of each of the plurality of reflected waves is a curve on a coordinate system with time or distance as a first axis and the intensity of the reflected wave as a second axis, and includes a first envelope and a second envelope different from the first envelope, and further includes a normalization unit that normalizes the second envelope using the first envelope as a reference so as to reduce errors caused by differences in mounting conditions of the plurality of distance sensors. A vehicle surroundings monitoring device according to one embodiment of the present disclosure includes an obstacle detection unit that detects obstacles around the vehicle based on differences in the envelopes of multiple reflected waves from a road around the vehicle, obtained by multiple distance sensors mounted on the vehicle, and each envelope of the multiple reflected waves is a curve on a coordinate system with time or distance as a first axis and the intensity of the reflected waves as a second axis, and includes a first envelope and a second envelope different from the first envelope, and further includes a road surface determination unit that determines that the first envelope can be used as the envelope of a reflected wave from the road in front of or behind the vehicle if the first envelope is within a predetermined threshold range on the coordinate system. A vehicle surroundings monitoring device according to one aspect of the present disclosure includes an obstacle detection unit that detects an obstacle around the vehicle based on differences in envelopes of a plurality of reflected waves from a road around the vehicle, the envelopes being obtained by a plurality of distance sensors mounted on the vehicle, and the envelopes of the plurality of reflected waves are curves on a coordinate system having a first axis representing time or distance and a second axis representing the intensity of the reflected waves, the curves including a first envelope, a second envelope different from the first envelope, and a third envelope different from the first envelope and the second envelope, and the first envelope is a curve of the road in front of or behind the vehicle, the first envelope being a curve of the road in front of or behind the vehicle, the first envelope being a curve of the road in front of or behind the vehicle, the second ... the second envelope is an envelope of a wave reflected from the road to the side of the vehicle obtained by a second distance sensor among the plurality of distance sensors; the third envelope is an envelope of a wave reflected from the road to the side of the vehicle obtained by a third distance sensor among the plurality of distance sensors; and the vehicle further comprises an angle derivation unit that derives an angle of the vehicle's traveling direction relative to the obstacle, and the angle derivation unit derives the angle of the vehicle's traveling direction based on the distance from the vehicle to the obstacle derived using the second envelope and the distance from the vehicle to the obstacle derived using the third envelope.

[0009] A vehicle surroundings monitoring method according to one aspect of the present disclosure detects an obstacle around a vehicle based on differences in envelopes of a plurality of reflected waves from a road around the vehicle, the reflected waves being obtained by a plurality of distance sensors mounted on the vehicle. A vehicle surroundings monitoring method, wherein the envelope of each of the plurality of reflected waves is a curve on a coordinate system with time or distance as a first axis and the intensity of the reflected wave as a second axis, and includes a first envelope and a second envelope different from the first envelope, and the second envelope is normalized based on the first envelope so as to reduce errors caused by differences in mounting conditions of the plurality of distance sensors. [Effects of the Invention]

[0011] According to the vehicle surroundings monitoring device and the like of the present disclosure, obstacles around the vehicle can be easily detected using a distance sensor. [Brief explanation of the drawings]

[0012] [Figure 1] 1 is a block diagram showing a vehicle periphery monitoring system including a vehicle periphery monitoring device according to a first embodiment. [Figure 2] FIG. 2 is a diagram showing an example of the mounting positions of distance sensors mounted on a vehicle. [Figure 3] 1 is a diagram illustrating an example of a road and obstacles detected by a vehicle periphery monitoring device; [Figure 4] 1A and 1B are diagrams illustrating an example of a reflected wave and an envelope obtained by a distance sensor for observing the area ahead of a vehicle. [Figure 5] 10A and 10B are diagrams illustrating an example of a reflected wave and an envelope obtained by a distance sensor for observing the side of a vehicle. [Figure 6] FIG. 10 is a diagram showing envelopes that appear depending on the presence or absence of obstacles on the road. [Figure 7] 4 is a flowchart showing the operation of the vehicle periphery monitoring device according to the first embodiment. [Figure 8] FIG. 10 is a block diagram showing a vehicle periphery monitoring system including a vehicle periphery monitoring device according to a second embodiment. [Figure 9] 1 is a diagram showing a first envelope, a second envelope, and a difference curve that is the difference between the first envelope and the second envelope. FIG. [Figure 10] 10 is a flowchart showing the operation of the vehicle periphery monitoring device according to the second embodiment. [Figure 11] FIG. 10 is a block diagram showing a vehicle periphery monitoring device according to a third embodiment. [Figure 12] FIG. 10 is a diagram showing a predetermined threshold value set for determining whether or not a road surface is normal. [Figure 13] 10 is a flowchart showing the operation of the vehicle periphery monitoring device according to the third embodiment. [Figure 14] FIG. 10 is a diagram showing a first envelope curve acquired by the vehicle periphery monitoring device of the fourth embodiment. [Figure 15] FIG. 10 is a block diagram showing a vehicle periphery monitoring device according to a fifth embodiment. [Figure 16] FIG. 2 is a diagram showing the positional relationship between a distance sensor mounted on a vehicle and an obstacle. [Figure 17] 10 is a flowchart showing the operation of the vehicle periphery monitoring device according to the fifth embodiment. [Figure 18] FIG. 13 is a block diagram showing a vehicle periphery monitoring system including a vehicle periphery monitoring device according to a sixth embodiment. [Figure 19] FIG. 10 is a diagram showing the positional relationship between a vehicle and an obstacle after a predetermined time has elapsed. [Figure 20] FIG. 13 is a block diagram showing a vehicle periphery monitoring system including a vehicle periphery monitoring device according to a seventh embodiment. [Figure 21] 13 is a flowchart showing the operation of the vehicle periphery monitoring device according to the seventh embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0013] The following embodiments will be described in detail with reference to the drawings. The embodiments described below are all comprehensive or specific examples. The numerical values, shapes, materials, components, component placement and connection configurations, steps, and step order shown in the following embodiments are merely examples and are not intended to limit the present disclosure. Furthermore, among the components in the following embodiments, components that are not recited in the independent claims that represent the highest concepts are described as optional components. Furthermore, each figure is a schematic diagram and is not necessarily an exact illustration. Furthermore, the same components are denoted by the same reference numerals in each figure. Furthermore, the present disclosure also includes embodiments realized by arbitrarily combining two or more of the multiple embodiments.

[0014] (Embodiment 1) [composition] The configuration of the vehicle periphery monitoring device 100 according to the first embodiment will be described.

[0015] FIG. 1 is a block diagram showing a vehicle periphery monitoring system 1 including a vehicle periphery monitoring device 100 according to the first embodiment.

[0016] As shown in FIG. 1, the vehicle periphery monitoring system 1 includes a plurality of distance sensors 11, 12, and 13 mounted on a vehicle 5, and a vehicle periphery monitoring device 100 that monitors the periphery of the vehicle 5.

[0017] The distance sensors 11 to 13 are each provided at a different position on the vehicle 5. Each of the distance sensors 11 to 13 is a sensor that emits a sensing wave, such as sound or light, toward the road and receives the wave reflected from the road. Each of the distance sensors 11 to 13 is, for example, an ultrasonic sensor, a radar, or a LiDAR (Light Detection and Ranging).

[0018] FIG. 2 is a diagram showing an example of the mounting positions of distance sensors 11 to 13 mounted on a vehicle 5. As shown in FIG.

[0019] 2 shows two first distance sensors 11, two second distance sensors 12, and two third distance sensors 13 as the multiple distance sensors 11 to 13. The distance sensors 11 to 13 shown in FIG. 1 are the distance sensors 11 to 13 located on the left side of the vehicle 5, out of the two distance sensors 11 to 13 shown in FIG. 2.

[0020] The distance sensor 11 is a sensor for observing the road ahead of the vehicle 5. The distance sensor 11 is provided on the front of the vehicle 5, such as on the bumper, and observes the road surface conditions ahead of the vehicle 5. The area ahead of the vehicle 5 is a driving surface, and it is considered unlikely that an obstacle Ob exists.

[0021] The distance sensor 12 is a sensor for observing the road on the side of the vehicle 5. The distance sensor 12 is provided on the side of the vehicle 5, such as on the side body or side mirror, and observes the road surface conditions on the side of the vehicle 5. One of the two sides is a road shoulder, where an obstacle Ob may be present.

[0022] The distance sensor 13 is a sensor for observing the road diagonally to the side of the vehicle 5 (in other words, diagonally forward). The distance sensor 13 is provided on a corner surface located between the front and side of the vehicle 5, and observes the road surface conditions diagonally to the side of the vehicle 5. One of the two diagonal sides is the driving surface and the road shoulder, where an obstacle Ob may be present. Note that hereinafter, the term "side" may refer to directions other than the front and rear of the vehicle 5, i.e., both the side and diagonal side of the vehicle 5.

[0023] FIG. 3 is a diagram showing an example of a road and an obstacle Ob detected by the vehicle periphery monitoring device 100. As shown in FIG.

[0024] Figure 3(a) shows a flat road without any obstacles Ob, Figure 3(b) shows a road with obstacles Ob such as gutters, and Figure 3(c) shows a road with obstacles Ob such as curbs.

[0025] The obstacle Ob is an object that is located on the road, such as a curb, a guardrail, a gutter, or a depression, and is an obstacle to the vehicle 5. The obstacle Ob has a shape that is different from the traveling surface.

[0026] The sensing results obtained by the distance sensors 11 to 13 will be explained using the distance sensors 11 and 12 as an example.

[0027] Fig. 4 is a diagram showing an example of a reflected wave R1 and an envelope W1 obtained by a distance sensor 11 for observing the area ahead of the vehicle 5. Fig. 5 is a diagram showing an example of a reflected wave R2 and an envelope W2 obtained by a distance sensor 12 for observing the area to the side of the vehicle 5.

[0028] Fig. 4(a) shows a sensing wave (direct wave) transmitted from the distance sensor 11. Fig. 5(a) shows a sensing wave transmitted from the distance sensor 12. Each sensing wave is transmitted from each of the distance sensors 11 and 12 at a cycle of, for example, 50 ms.

[0029] FIG. 4(b) shows a reflected wave R1 reflected from the road (road surface) ahead of the vehicle 5. In this example, the reflected wave R1 reflected from a relatively flat road is shown. FIG. 5(b) shows a reflected wave R2 reflected from the road to the side of the vehicle 5. In this example, the reflected wave R2 is shown when there is a depression in the road to the side of the vehicle 5.

[0030] Figure 4(c) shows the reflected wave R1 received by the distance sensor 11, and Figure 5(c) shows the reflected wave R2 received by the distance sensor 12. Each of the reflected waves R1 and R2 is represented as a waveform curve on a coordinate system with time as the first axis (horizontal axis) and power, which is the strength of the reflected waves R1 and R2, as the second axis (vertical axis).

[0031] FIG. 4(d) shows the envelope W1 obtained by performing the Hilbert transform on the reflected wave R1 shown in FIG. 4(c). FIG. 5(d) shows the envelope W2 obtained by performing the Hilbert transform on the reflected wave R2 shown in FIG. 5(c). Each envelope W1, W2 is expressed as a curve on a coordinate system with time as the first axis and power, which is the strength of the reflected waves R1, R2, as the second axis. As shown in FIG. 4(d), when there is no obstacle Ob on the road, the envelope W1 is a gentle curve. However, as shown in FIG. 5(d), when a depression is present on the road, the envelope W2 is a curve with a concave shape.

[0032] Although the distance sensors 11 and 12 have been described above as an example, the same applies to the distance sensor 13. The sensing results detected by the distance sensors 11 to 13 are output to the vehicle periphery monitoring device 100.

[0033] The vehicle periphery monitoring device 100 includes an obstacle detection unit 101 that detects an obstacle Ob around the vehicle 5, and a memory 102.

[0034] The memory 102 stores information about the mounting positions of the distance sensors 11 to 13 on the vehicle 5. The memory 102 also stores a software program. The functions of the obstacle detection unit 101 and the like provided in the vehicle periphery monitoring device 100 are realized by operating the software program.

[0035] The obstacle detection unit 101 detects an obstacle Ob using the sensing results obtained by the distance sensors 11 to 13. For example, the obstacle detection unit 101 detects the obstacle Ob based on the rate of change of the envelope W2 of the reflected wave R2 from the road around the vehicle 5, which is obtained by the distance sensor 12.

[0036] FIG. 6 is a diagram showing an envelope W2 that appears depending on the presence or absence of an obstacle Ob on the road.

[0037] FIG. 6(a) shows the envelope curve W2 when there is no obstacle Ob on the road. FIG. 6(b) shows the envelope curve W2 when there is a protruding obstacle Ob, such as a curb, on the road. FIG. 6(c) shows the envelope curve W2 when there is a depression-like obstacle Ob, such as a road ditch, on the road. Each envelope curve W2 is represented as a curve on a coordinate system with the horizontal distance from the distance sensor 12 provided on the side of the vehicle 5 as the first axis and the power (peak value) of the reflected wave R2 as the strength of the reflected wave R2 as the second axis. The horizontal distance from the distance sensor 12 is calculated based on the time from when the sensing wave is emitted until the reflected wave R2 returns and the height coordinate of the distance sensor 12. In this embodiment, the horizontal distance from the distance sensor 12 is treated as the distance from the side of the vehicle 5 when the vehicle 5 is viewed from above, and the distance from the side of the vehicle 5 is referred to as the distance from the vehicle 5.

[0038] The obstacle detection unit 101 detects the rate of change of the envelope W2 of the reflected wave R2 obtained by the distance sensor 12. The rate of change of the envelope W2 is calculated, for example, based on the amount of change in power over a predetermined distance. For example, as shown in FIG. 6(a), the obstacle detection unit 101 determines that there is no obstacle Ob when the amount of change in power is small overall, i.e., when the rate of change is small. Furthermore, as shown in FIGS. 6(b) and 6(c), the obstacle detection unit 101 determines that there is an obstacle Ob when there are areas where the amount of change in power is large, i.e., when there are areas where the rate of change is large.

[0039] Furthermore, as shown in (b) of Fig. 6, when the power of the envelope W2 changes in the positive direction, the obstacle detection unit 101 determines that a protruding obstacle Ob exists at the point of change. Furthermore, as shown in (c) of Fig. 6, when the power of the envelope W2 changes in the negative direction, the obstacle detection unit 101 determines that a depression-like obstacle Ob exists at the point of change. The results of detection and determination by the obstacle detection unit 101 are output to an external alarm device or the like.

[0040] According to this configuration, for example, the obstacle Ob can be detected using a distance sensor (for example, the distance sensor 12) already mounted on the vehicle 5. This makes it possible to easily detect obstacles around the vehicle 5.

[0041] [Operation] The operation of the vehicle periphery monitoring device 100 according to the first embodiment will be described.

[0042] FIG. 7 is a flowchart showing the operation of the vehicle periphery monitoring device 100.

[0043] First, the vehicle periphery monitoring device 100 acquires an envelope of a wave reflected from a road around the vehicle 5 from a distance sensor mounted on the vehicle 5 (step S110). Specifically, the vehicle periphery monitoring device 100 acquires an envelope W2 of a wave R2 reflected from a road to the side of the vehicle 5 from the distance sensor 12 provided on the side of the vehicle 5.

[0044] Next, the obstacle detection unit 101 detects an obstacle Ob around the vehicle 5 based on the acquired envelope W2 (step S120). The obstacle detection unit 101 detects the presence or absence of an obstacle Ob on the side of the vehicle 5 based on the magnitude of the rate of change of the envelope W2. Furthermore, if the power of the envelope W2 is changing in the positive direction, the obstacle detection unit 201 determines that a protrusion-like obstacle Ob is present on the side of the vehicle 5. Furthermore, if the power of the envelope W2 is changing in the negative direction, the obstacle detection unit 101 determines that a depression-like obstacle Ob is present on the side of the vehicle 5.

[0045] Thereafter, the processes shown in steps S110 and S120 are repeatedly executed. According to this method, for example, the obstacle Ob can be detected using the distance sensor 12 already mounted on the vehicle 5. This makes it possible to easily detect obstacles around the vehicle 5.

[0046] [Effects, etc.] The vehicle surroundings monitoring device 100 of this embodiment is equipped with an obstacle detection unit 101 that detects an obstacle Ob around the vehicle 5 based on the rate of change of the envelope W2 of the reflected wave R2 for the road around the vehicle 5, obtained by a distance sensor (e.g., distance sensor 12) mounted on the vehicle 5.

[0047] According to this configuration, for example, the obstacle Ob can be detected using the distance sensor 12 that is already mounted on the vehicle 5. This makes it possible to easily detect obstacles around the vehicle 5.

[0048] The vehicle surroundings monitoring method of this embodiment detects obstacles around the vehicle 5 based on the rate of change of the envelope W2 of the reflected wave R2 relative to the road around the vehicle 5, obtained by the distance sensor 12 mounted on the vehicle 5.

[0049] According to this method, for example, the obstacle Ob can be detected using the distance sensor 12 already mounted on the vehicle 5. This makes it possible to easily detect obstacles around the vehicle 5.

[0050] Although the above example shows that two of each of the distance sensors 11, 12, and 13 are mounted on the vehicle 5, this is not limiting, and each of the distance sensors 11, 12, and 13 may be mounted on the vehicle 5 alone. Although the above example shows that both of the distance sensors 12 and 13 are mounted on the vehicle 5, this is not limiting, and it is sufficient that the vehicle 5 is mounted with at least one of the distance sensors 12 and 13. Furthermore, the vehicle 5 may be provided with other distance sensors for observing the rear of the vehicle 5, the rear lateral side of the vehicle 5, and the rear diagonal lateral side of the vehicle 5.

[0051] In addition, although the above example shows that the distance sensor 12 outputs the sensing result related to the envelope W2 to the vehicle periphery monitoring device 100, the present invention is not limited to this. For example, when the sensing result related to the reflected wave R2 is output from the distance sensor 12 to the vehicle periphery monitoring device 100, the vehicle periphery monitoring device 100 may generate information related to the envelope W2 based on the acquired reflected wave R2, and detect the obstacle Ob based on the generated envelope W2. The same applies to the distance sensors 11 and 13.

[0052] (Embodiment 2) [composition] The configuration of a vehicle periphery monitoring device 200 according to a second embodiment will be described. In the second embodiment, an example will be described in which an obstacle Ob is detected based on the difference between the envelopes of a plurality of reflected waves, and the distance from the vehicle 5 to the obstacle Ob is calculated. In the second embodiment, an example will be described in which the envelopes are normalized.

[0053] Hereinafter, some or all of the multiple reflected waves obtained by multiple distance sensors may be referred to as reflected waves R, and some or all of the multiple envelopes corresponding to each of the multiple reflected waves may be referred to as envelopes W.

[0054] FIG. 8 is a block diagram showing a vehicle periphery monitoring system 1 including a vehicle periphery monitoring device 200 according to the second embodiment.

[0055] The vehicle periphery monitoring system 1 includes a plurality of distance sensors 11, 12, and 13 mounted on a vehicle 5, and a vehicle periphery monitoring device 200 that monitors the periphery of the vehicle 5. Each of the distance sensors 11 to 13 is the same as in the first embodiment.

[0056] The vehicle periphery monitoring device 200 according to the second embodiment includes a normalization unit 203 that normalizes the envelope W, an obstacle detection unit 201 that detects an obstacle Ob, and a memory 102. The memory 102 is the same as that in the first embodiment. First, the obstacle detection unit 201 will be described.

[0057] The obstacle detection unit 201 detects an obstacle Ob around the vehicle 5 based on the difference between the envelopes W of the multiple reflected waves R from the road around the vehicle 5 obtained by the multiple distance sensors 11-13.

[0058] 9 is a diagram showing a first envelope W1, a second envelope W2, and a difference curve Wd which is the difference between the first envelope W1 and the second envelope W2. Each of the envelopes W1 and W2 is represented as a curve on a coordinate system in which the first axis represents the distance from the vehicle 5 and the second axis represents the power, which is the strength of the reflected waves R1 and R2.

[0059] 9(a) is the envelope of the reflected wave R from the road ahead of the vehicle 5, obtained by the first distance sensor 11. This first envelope curve W1 shows a state when no obstacle Ob is detected ahead of the vehicle 5.

[0060] 9(b) is the envelope of the wave R reflected from the road on the side of the vehicle 5, obtained by the second distance sensor 12. The second envelope W2 shows the state when a depression-like obstacle Ob is detected on the side of the vehicle 5.

[0061] The differential curve Wd shown in Figure 9(c) is obtained by calculating the difference between the first envelope curve W1 and the second envelope curve W2. Specifically, this differential curve Wd is obtained by subtracting the first envelope curve W1 from the second envelope curve W2.

[0062] The fault detection unit 201 compares the first envelope W1 with the second envelope W2 and determines whether the difference between the first envelope W1 and the second envelope W2 is equal to or greater than a predetermined threshold TH. obj If the difference between the first envelope W1 and the second envelope W2 is greater than the threshold value TH, it is determined that an obstacle Ob is present. The reason for taking the difference between the first envelope W1 and the second envelope W2 is to perform a highly accurate determination according to the road surface conditions. obj is a value determined in advance based on the shape, size, material, etc. of the obstacle Ob, and is set on the positive and negative sides with power 0 (zero) as the reference. objand the negative threshold TH obj may be the same value or may be different values.

[0063] Furthermore, the obstacle detection unit 201 derives the distance D2 from the vehicle 5 to the obstacle Ob based on the difference curve Wd. As shown in (c) of FIG. 9, the obstacle detection unit 201 calculates the distance D2 from the vehicle 5 to the obstacle Ob when the power of the difference curve Wd is greater than or equal to the threshold TH obj The point where the obstacle Ob is first exceeded is defined as the distance to the obstacle Ob, D2.

[0064] For example, the fault detection unit 201 detects whether the power of the differential curve Wd is greater than or equal to a negative threshold TH obj For example, the obstacle detection unit 201 determines that a depression-like object exists at the point where the power of the difference curve Wd exceeds the positive threshold TH and sets the point as the distance D2 to the obstacle Ob (see (c) of FIG. 9). obj It is determined that a protruding object exists at the point where the distance exceeds the obstacle Ob for the first time, and the point is set as the distance D2 to the obstacle Ob (not shown).

[0065] The obstacle detection unit 201 also derives the width L2 of the obstacle Ob based on the difference curve Wd. The width L2 of the obstacle Ob is the length of the obstacle Ob in the direction away from the side of the vehicle 5. The obstacle detection unit 201 first calculates the width L2 of the obstacle Ob based on the difference curve Wd. obj From the point where the power of the difference curve Wd exceeds the threshold TH obj The distance to the point where the difference curve Wd returns to the range of the threshold TH is the width L2. obj If the obstacle does not return within the range, the width dimension L2 may be set to the range that can be measured by the distance sensor 12. The detection result detected by the obstacle detection unit 201 is output to an external notification device or the like.

[0066] Next, a description will be given of the normalization unit 203 that normalizes the envelope W. The normalization process of the envelope W is executed before the obstacle detection unit 201 detects the obstacle Ob.

[0067] The distance to the road surface and directional attenuation characteristics of each of the distance sensors 11-13 provided on the vehicle 5 change depending on the position, height, orientation, etc., at which the sensors are mounted on the vehicle 5. Therefore, the data of each envelope W obtained by each of the distance sensors 11-13 contains errors due to differences in mounting conditions. Therefore, the normalization unit 203 normalizes one envelope W based on the other envelope W so as to reduce errors in the multiple envelopes W caused by differences in mounting conditions of the distance sensors 11-13.

[0068] For example, to normalize the second envelope W2 using the first envelope W1 as a reference, the normalization unit 203 multiplies the envelope W2 by a normalization term k as shown in the following (Equation 1) to derive the normalized envelope W2'.

[0069]

number

[0070] The normalization term k is set appropriately based on the specifications of the distance sensors 11 and 12 or the actual measurement values ​​of the road surface using the distance sensors 11 and 12. Note that hereinafter, the normalized envelope W2' will also be referred to as the envelope W2. Information related to the normalized envelope W2 is output to the obstacle detection unit 201. The obstacle detection unit 201 detects an obstacle Ob around the vehicle 5 by comparing the envelope W1 with the normalized envelope W2.

[0071] According to the vehicle periphery monitoring device 200 of the second embodiment, for example, an obstacle Ob can be detected using a plurality of distance sensors (e.g., distance sensors 11 and 12) already mounted on the vehicle 5. This allows for easy detection of obstacles around the vehicle 5. Furthermore, since the obstacle Ob is detected based on the difference between the envelopes W1 and W2 obtained from the plurality of distance sensors 11 and 12, the obstacle Ob can be detected with high accuracy. Furthermore, since the normalized envelope W2 is used, the obstacle Ob can be detected with high accuracy.

[0072] Although the above example shows that the normalization unit 203 normalizes the second envelope W2 based on the first envelope W1, the present invention is not limited to this. For example, the normalization unit 203 may normalize the first envelope W1 based on the second envelope W2. Furthermore, the above example shows that information related to the envelope W2 corresponding to one distance sensor 12 is output to the fault detection unit 201, but the present invention is not limited to this. For example, the normalization unit 203 may normalize each envelope W corresponding to multiple distance sensors 11, 13 and output each normalized envelope W to the fault detection unit 201.

[0073] [Operation] The operation of the vehicle periphery monitoring device 200 according to the second embodiment will be described.

[0074] FIG. 10 is a flowchart showing the operation of the vehicle periphery monitoring device 200.

[0075] First, the vehicle periphery monitoring device 200 acquires the envelope of the reflected wave from the road around the vehicle 5 from a plurality of distance sensors mounted on the vehicle 5 (step S210). Specifically, the vehicle periphery monitoring device 200 acquires the first envelope W1 of the reflected wave R1 from the road ahead of the vehicle 5 from the distance sensor 11, and acquires the second envelope W2 of the reflected wave R2 from the road to the side of the vehicle 5 from the distance sensor 12.

[0076] Next, the normalization unit 203 normalizes the second envelope W2 using the first envelope W1 as a reference so as to reduce errors caused by differences in the mounting conditions of the multiple distance sensors 11 and 12 (step S220). The normalization unit 203 outputs the normalized second envelope W2 to the fault detection unit 201.

[0077] Next, the obstacle detection unit 201 determines whether or not there is an obstacle Ob around the vehicle 5 based on the first envelope W1 and the normalized second envelope W2 acquired from the distance sensor 11 (step S230).

[0078] The fault detection unit 201 determines whether the difference between the first envelope W1 and the second envelope W2 is equal to a predetermined threshold THobj If the difference is smaller than , it is determined that there is no obstacle Ob (No in S230), and the flow shown in FIG. 10 ends.

[0079] On the other hand, the fault detection unit 201 detects that the difference between the first envelope W1 and the second envelope W2 is equal to a predetermined threshold TH obj If the power of the difference curve Wd is greater than a predetermined positive threshold TH, the obstacle detection unit 201 determines that an obstacle Ob is present (Yes in S230). obj If the value is above this, it is determined to be a protruding obstacle Ob, and the value is set to the predetermined negative threshold -TH obj If the value is below, it is determined to be a depression-like obstacle Ob.

[0080] The obstacle detection unit 201 also derives the distance D2 from the vehicle 5 to the obstacle Ob and the width L2 of the obstacle Ob based on the difference curve Wd, which is the difference between the first envelope W1 and the second envelope W2 (step S240).

[0081] In addition, if the obstacle Ob is depression-shaped and the width dimension L2 of the obstacle Ob is equal to or less than a specific threshold value (e.g., the tire width), the obstacle detection unit 201 may determine that the detected obstacle Ob is not a problematic obstacle Ob, since there is no possibility that the vehicle 5 will derail.

[0082] Furthermore, when the obstacle detection unit 201 detects multiple obstacles Ob using multiple distance sensors, it may determine that the obstacle Ob closest to the vehicle 5 is the problematic obstacle Ob, and derive the distance to this obstacle Ob and the width dimension of the obstacle Ob.

[0083] Thereafter, the processes shown in steps S210 to S240 are repeatedly executed. According to this method, for example, the obstacle Ob can be detected using a distance sensor already mounted on the vehicle 5. This makes it possible to easily detect obstacles around the vehicle 5.

[0084] [Effects, etc.] The vehicle surroundings monitoring device 200 of this embodiment includes an obstacle detection unit 201 that detects an obstacle Ob around the vehicle 5 based on the difference between the envelopes W1, W2 of multiple reflected waves R1, R2 from the road around the vehicle 5 obtained by multiple distance sensors (e.g., distance sensors 11, 12) mounted on the vehicle 5.

[0085] According to this configuration, for example, the obstacle Ob can be detected using the multiple distance sensors 11, 12 already mounted on the vehicle 5. This makes it possible to easily detect obstacles around the vehicle 5. Furthermore, since the obstacle Ob is detected based on the difference between the envelopes W1, W2 obtained from the multiple distance sensors 11, 12, the obstacle Ob can be detected with high accuracy.

[0086] Furthermore, the envelopes of each of the multiple reflected waves R1, R2 may be curves on a coordinate system with time or distance as the first axis and the intensity of the reflected waves R1, R2 as the second axis, and may include a first envelope W1 and a second envelope W2 different from the first envelope W1.

[0087] According to this configuration, the obstacle Ob can be detected based on the difference between the first envelope W1 and the second envelope W2 obtained from the multiple distance sensors 11 and 12. This allows the obstacle Ob to be detected with high accuracy using the distance sensors 11 and 12.

[0088] Furthermore, the first envelope W1 may be the envelope of the reflected wave R1 from the road in front of or behind the vehicle 5, obtained by the first distance sensor 11 of the multiple distance sensors, and the second envelope W2 may be the envelope of the reflected wave R2 from the road to the side of the vehicle 5, obtained by the second distance sensor 12 of the multiple distance sensors.

[0089] According to this configuration, the obstacle Ob can be detected based on the difference between the first envelope W1 corresponding to the road in front of or behind the vehicle 5 and the second envelope W2 corresponding to the road on the side of the vehicle 5. This allows the obstacle Ob to be detected with high accuracy using the distance sensors 11 and 12.

[0090] The fault detection unit 201 also calculates a difference between the first envelope W1 and the second envelope W2 as a predetermined threshold TH obj If the difference is larger than , it may be determined that an obstacle Ob is present.

[0091] This configuration makes it possible to perform highly accurate determinations according to road surface conditions, thereby enabling the distance sensors 11 and 12 to detect the obstacle Ob with high accuracy.

[0092] The obstacle detection unit 201 may also derive the distance D2 from the vehicle 5 to the obstacle Ob based on a difference curve Wd that is the difference between the first envelope W1 and the second envelope W2.

[0093] According to this configuration, the distance D2 from the vehicle 5 to the obstacle Ob can be easily calculated using the distance sensors 11 and 12.

[0094] The obstacle detection unit 201 may also derive the width L2 of the obstacle Ob based on a difference curve Wd that is the difference between the first envelope W1 and the second envelope W2.

[0095] According to this configuration, the distance sensors 11 and 12 can be used to easily derive the width L2 of the obstacle Ob.

[0096] Furthermore, the vehicle periphery monitoring device 200 may further normalize the second envelope W2 using the first envelope W1 as a reference so as to reduce errors caused by differences in the mounting conditions of the multiple distance sensors 11, 12.

[0097] According to this configuration, the obstacle Ob can be detected using the normalized envelope W2, thereby enabling the obstacle Ob to be detected with high accuracy.

[0098] The distance sensors 11 and 12 may also be ultrasonic sensors, radars or lidars.

[0099] According to this, the obstacle Ob can be detected using an ultrasonic sensor, radar, or lidar, thereby making it possible to easily detect obstacles around the vehicle 5.

[0100] The vehicle surroundings monitoring method of this embodiment detects an obstacle Ob around the vehicle 5 based on the difference between the envelopes W1, W2 of multiple reflected waves R1, R2 from the road around the vehicle 5 obtained by multiple distance sensors (e.g., distance sensors 11, 12) mounted on the vehicle 5.

[0101] According to this method, for example, an obstacle Ob can be detected using a plurality of distance sensors 11, 12 already mounted on the vehicle 5. This makes it possible to easily detect obstacles around the vehicle 5. Furthermore, since the obstacle Ob is detected based on the difference between the envelopes W1, W2 obtained from the plurality of distance sensors 11, 12, the obstacle Ob can be detected with high accuracy.

[0102] (Embodiment 3) [composition] The configuration of a vehicle periphery monitoring device 300 according to a third embodiment will be described. For example, when a vehicle 5 is tilted obliquely, the distance sensor 11 provided on the front of the vehicle 5 may detect an obstacle Ob located diagonally to the side. In this case, the envelope W1 obtained by the distance sensor 11 may have a waveform curve similar to that of the envelope W2, and the method of calculating the difference between the envelopes W1 and W2 may not be able to accurately detect the obstacle Ob. Therefore, in the third embodiment, an example will be described in which the envelope W1 obtained by the distance sensor 11 is determined to be usable as data of a normal road surface, and then the obstacle Ob is detected.

[0103] Fig. 11 is a block diagram showing a vehicle periphery monitoring device 300 according to the third embodiment. Note that Fig. 11 shows distance sensors 11, 12, and 13 similar to those in the second embodiment.

[0104] The vehicle periphery monitoring device 300 according to the third embodiment includes a road surface determination unit 304, a normalization unit 203, an obstacle detection unit 201, and a memory 102.

[0105] The memory 102 of the third embodiment stores a predetermined threshold value set for determining whether or not the road surface is a normal road surface.

[0106] FIG. 12 is a diagram showing predetermined threshold values ​​set for determining whether or not a road surface is normal.

[0107] The predetermined thresholds are set in the memory 102 as upper and lower thresholds, as shown in Fig. 12. The upper and lower thresholds are set to follow the standard envelope Ws at predetermined intervals from the standard envelope Ws. The standard envelope Ws and the predetermined thresholds are set appropriately based on actual measurements of the road surface using the distance sensor 11.

[0108] The road surface determination unit 304 determines that the first envelope W1 obtained by the distance sensor 11 can be used as the envelope of the reflected wave R1 from the road ahead of the vehicle 5 when the first envelope W1 obtained by the distance sensor 11 is within a predetermined threshold range on the coordinates shown in Figure 12, i.e., between the upper threshold and the lower threshold.

[0109] The road surface determination unit 304 outputs information about the first envelope W1 determined to be usable to the obstacle detection unit 201. The obstacle detection unit 201 detects an obstacle Ob using the first envelope W1 output from the road surface determination unit 304. The road surface determination unit 304 also outputs the information about the first envelope W1 to the memory 102 for storage. The information about the first envelope W1 stored in the memory 102 is used as a substitute for the first envelope W1 obtained by the distance sensor 11, for example, when the first envelope W1 cannot be used as normal road surface data. In other words, when the first envelope W1 is not within a predetermined threshold range, the road surface determination unit 304 outputs the past first envelope W1 stored in the memory 102 as the envelope of the reflected wave R1 from the road ahead of the vehicle 5.

[0110] [Operation] The operation of the vehicle periphery monitoring device 300 according to the third embodiment will be described.

[0111] FIG. 13 is a flowchart showing the operation of the vehicle periphery monitoring device 300.

[0112] First, the vehicle periphery monitoring device 300 acquires the first envelope curve W1 from the distance sensor 11, and also acquires the second envelope curve W2 from the distance sensor 12 (step S310).

[0113] Next, the road surface determination unit 304 determines whether the first envelope W1 obtained by the distance sensor 11 is within a predetermined threshold range (step S320). The determination in step S320 is performed whenever necessary while the vehicle 5 and the vehicle periphery monitoring device 300 are in operation.

[0114] If the first envelope W1 is within the predetermined threshold range (Yes in S320), the road surface determination unit 304 determines that the first envelope W1 can be used as data for a normal road surface, and outputs information about this first envelope W1 to the obstacle detection unit 201 (step S330).The road surface determination unit 304 also outputs the information about this first envelope W1 to the memory 102 and stores it in the memory 102 (step S340).

[0115] On the other hand, if the first envelope W1 is not within the predetermined threshold range (No in S320), the road surface determination unit 304 determines that the first envelope W1 cannot be used as normal road surface data. In this case, the road surface determination unit 304 reads information about the past first envelope W1 stored in the memory 102, and outputs the information about the past first envelope W1 to the obstacle detection unit 201 (step S350). Thereafter, steps S220 to S240 of the second embodiment are executed.

[0116] [Effects, etc.] The vehicle surroundings monitoring device 300 of this embodiment further includes a road surface determination unit 304 that determines that the first envelope W1 can be used as the envelope of the reflected wave from the road in front of or behind the vehicle 5 when the first envelope W1 is within a predetermined threshold range on the coordinate system (coordinate system having a first axis and a second axis).

[0117] This configuration makes it possible to determine whether the first envelope W1 obtained by the distance sensor 11 can be used as data for a normal road surface. Therefore, even if the vehicle 5 is tilted at an angle, for example, it becomes possible to detect the obstacle Ob. This makes it possible to correctly detect the obstacle Ob.

[0118] In addition, if the first envelope W1 is within a predetermined threshold range on the above coordinates, the road surface determination unit 304 may output the first envelope W1 as the envelope of the reflected wave R1 from the road in front of or behind the vehicle 5 and store it in memory 102, and if the first envelope W1 is not within the predetermined threshold range, the road surface determination unit 304 may output the past first envelope W1 stored in memory 102 as the envelope of the reflected wave R1 from the road in front of or behind the vehicle 5.

[0119] According to this configuration, even if the vehicle 5 is tilted obliquely, the obstacle Ob can be detected using information about the past first envelope W1. This allows the obstacle Ob to be detected correctly.

[0120] (Fourth embodiment) [composition] The configuration of a vehicle periphery monitoring device 400 according to a fourth embodiment will be described. For example, in the third embodiment, if the first envelope W1 obtained by the distance sensor 11 cannot be used as data on a normal road surface, time is required to read out past data on the first envelope W1 from the memory 102. Therefore, in the fourth embodiment, an example will be described in which the detection time is shortened by detecting an obstacle Ob using a usable portion of the first envelope W1 obtained by the distance sensor 11.

[0121] The vehicle periphery monitoring device 400 according to the fourth embodiment includes, as in the third embodiment, a road surface determination unit 304, a normalization unit 203, an obstacle detection unit 201, and a memory 102 (see FIG. 11).

[0122] When the entire first envelope W1 is within a predetermined threshold range on the coordinate system, the road surface determination unit 304 outputs the first envelope W1 as an envelope of a normal road surface, as in embodiment 3. On the other hand, when a part of the first envelope W1 is not within the predetermined threshold range, the road surface determination unit 304 performs the following process.

[0123] FIG. 14 is a diagram showing the first envelope W1 acquired by the vehicle periphery monitoring device 400. As shown in FIG.

[0124] FIG. 14 shows an example in which a part of the first envelope W1 exceeds the upper threshold value, and the remaining part is within the range of the predetermined threshold value.

[0125] When a part of the first envelope W1 is not within a predetermined threshold range, the road surface determination unit 304 of the fourth embodiment outputs the envelope of the remaining part of the first envelope W1 excluding that part as the envelope of the reflected wave R1 from the road ahead of the vehicle 5. In other words, the road surface determination unit 304 regards the envelope of the remaining part of the first envelope W1 excluding that part as data of a normal road surface, and outputs information about the envelope of the remaining part to the obstacle detection unit 201.

[0126] In order to regard the envelope of the remaining portion as data of a normal road surface, it is desirable that the distance of the envelope of the remaining portion in the first axis (horizontal axis) direction is a distance sufficient to ensure the safety of the vehicle 5.

[0127] [Effects, etc.] The road surface judgment unit 304 of embodiment 4 outputs the first envelope W1 as the envelope of the reflected wave R1 from the road in front of or behind the vehicle 5 when the entire first envelope W1 is within a predetermined threshold range on the coordinate system, and outputs the envelope of the remaining part of the first envelope W1 excluding that part as the envelope of the reflected wave R1 from the road in front of or behind the vehicle 5 when a part of the first envelope W1 is not within the predetermined threshold range.

[0128] In this way, when a part of the first envelope W1 is not within the predetermined threshold range, the remaining part of the envelope is used, eliminating the need to read information about the past first envelope W1 from the memory 102. This reduces the time required to detect the obstacle Ob.

[0129] (Embodiment 5) [composition] A description will be given of the configuration of a vehicle periphery monitoring device 500 according to the fifth embodiment. In the fifth embodiment, an example in which the angle θ of the traveling direction of a vehicle 5 is derived will be described.

[0130] FIG. 15 is a block diagram showing a vehicle periphery monitoring device 500 according to the fifth embodiment.

[0131] Vehicle periphery monitoring device 500 includes angle derivation unit 505, road surface determination unit 304, normalization unit 203, obstacle detection unit 201, and memory 102. Road surface determination unit 304, normalization unit 203, obstacle detection unit 201, and memory 102 are the same as those in the fourth embodiment.

[0132] The angle derivation unit 505 derives the angle θ of the traveling direction of the vehicle 5 relative to the obstacle Ob. In the fifth embodiment, the angle θ of the traveling direction of the vehicle 5 is derived using the second envelope W2 and the third envelope W3. The third envelope W3 is the envelope of the reflected wave R3 from the road to the side of the vehicle 5, obtained by the third distance sensor 13. Note that the envelope W described here is the envelope of the reflected wave R returning in a direction perpendicular to the obstacle Ob when the vehicle 5 is viewed from above.

[0133] FIG. 16 is a diagram showing the positional relationship between the distance sensors 12 and 13 mounted on the vehicle 5 and the obstacle Ob.

[0134] Fig. 16(a) shows an example in which the vehicle 5 travels at an angle θ with respect to an obstacle Ob. The mounting positions of the distance sensors 12 and 13 are expressed in coordinates in which the intersection of the rear wheel axle of the vehicle 5 and the center line of the vehicle 5 is the origin 0, the traveling direction of the vehicle 5 is the X axis, and the width direction of the vehicle 5 is the Y axis. Fig. 16(b) shows a diagram focusing on the positional relationship between the distance sensors 12 and 13 and the obstacle Ob.

[0135] The angle derivation unit 505 acquires information about the mounting positions of the distance sensors 12 and 13 stored in the memory 102. Then, the angle derivation unit 505 derives the angle θ based on the distance D2 from the vehicle 5 to the obstacle Ob derived using the second envelope W2 and the distance D3 from the vehicle 5 to the obstacle Ob derived using the third envelope W3.

[0136] [Operation] The operation of the vehicle periphery monitoring device 500 according to the fifth embodiment will be described.

[0137] FIG. 17 is a flowchart showing the operation of the vehicle periphery monitoring device 500.

[0138] The angle derivation unit 505 acquires the distances D2 and D3 from the vehicle 5 to the obstacle Ob, which are acquired by the obstacle detection unit 201 (step S510). The angle derivation unit 505 also acquires the mounting position (X12, Y12) of the distance sensor 12 and the mounting position (X13, Y13) of the distance sensor 13, which are stored in the memory 102 (step S520). The angle derivation unit 505 also calculates the angle θ of the traveling direction of the vehicle 5 relative to the obstacle Ob by substituting the values ​​acquired in steps S510 and S520 into the following (Equation 2) (step S530).

[0139]

number

[0140] The reason why (Equation 2) is an approximation is that in (b) of Figure 16, the distance sensors 12 and 13 may not be arranged on a straight line. Even in that case, as shown in (Equation 3), by setting the difference (Y13-Y12) in the mounting positions of the distance sensors 12 and 13 to be sufficiently smaller than the distance D3 or D2, the angle θ can be derived using (Equation 2), which is an approximation.

[0141]

number

[0142] [Effects, etc.] The vehicle periphery monitoring device 500 of the fifth embodiment further includes an angle derivation unit 505 that derives an angle θ of the traveling direction of the vehicle 5 relative to the obstacle Ob. The envelopes of each of the multiple reflected waves further include a third envelope W3 different from the first envelope W1 and the second envelope W2, and the third envelope W3 is the envelope of the reflected wave R3 from the road to the side of the vehicle 5, obtained by a third distance sensor 13 out of the multiple distance sensors 11 to 13. The angle derivation unit 505 derives the angle θ of the traveling direction of the vehicle 5 based on a distance D2 from the vehicle 5 to the obstacle Ob derived using the second envelope W2 and a distance D3 from the vehicle 5 to the obstacle Ob derived using the third envelope W3.

[0143] In this way, by equipping the vehicle surroundings monitoring device 500 with the angle derivation unit 505, the angle θ of the vehicle 5's direction of travel relative to the obstacle Ob can be easily derived using the second distance sensor 12 and the third distance sensor 13.

[0144] (Embodiment 6) [composition] A description will be given of the configuration of a vehicle periphery monitoring device 600 according to embodiment 6. In embodiment 6, an example will be described in which the distance between a vehicle 5 and an obstacle Ob after a predetermined time has elapsed from a predetermined time is predicted.

[0145] FIG. 18 is a block diagram showing a vehicle periphery monitoring system 1A including a vehicle periphery monitoring device 600. As shown in FIG.

[0146] The vehicle periphery monitoring system 1A includes a plurality of distance sensors 11, 12, and 13, and a vehicle periphery monitoring device 600 that monitors the periphery of a vehicle 5. The distance sensors 11 to 13 are the same as those in the first embodiment. The vehicle periphery monitoring system 1A also includes a speed sensor 50 and a steering angle sensor 60.

[0147] The vehicle periphery monitoring device 600 according to the sixth embodiment includes a distance prediction unit 606, an angle derivation unit 505, a road surface determination unit 304, a normalization unit 203, an obstacle detection unit 201, and a memory 102. The angle derivation unit 505, the road surface determination unit 304, the normalization unit 203, the obstacle detection unit 201, and the memory 102 are the same as those in the fifth embodiment.

[0148] The distance prediction unit 606 predicts the distance between the vehicle 5 and the obstacle Ob after a predetermined time has elapsed from a predetermined time based on information relating to the speed and steering angle of the vehicle 5.

[0149] FIG. 19 is a diagram showing the positional relationship between the vehicle 5 and the obstacle Ob after a predetermined time has elapsed.

[0150] The lower diagram of FIG. 19(a) shows the position of the vehicle 5 at a given time and the distance D to the obstacle Ob. meaThe figure above shows the position of the vehicle 5 and the distance D to the obstacle Ob after a predetermined time t has elapsed from a predetermined time. pre 19(b) shows a diagram in which the velocity v of the vehicle 5 is resolved into a component parallel to the obstacle Ob and a component perpendicular to the obstacle Ob.

[0151] The distance prediction unit 606 obtains the distances D2 and D3 from the vehicle 5 to the obstacle Ob calculated by the angle derivation unit 505, and the angle θ of the traveling direction of the vehicle 5 with respect to the obstacle Ob. The distance prediction unit 606 determines the shorter of the obtained distances D2 and D3 as the minimum distance D mea The distance prediction unit 606 also acquires the speed v of the vehicle 5 from the speed sensor 50 and the steering angle θ of the vehicle 5 from the steering angle sensor 60. str Then, the distance prediction unit 606 obtains the distance D between the vehicle 5 and the obstacle Ob after a predetermined time t has elapsed from the predetermined time. pre is calculated using the following (Equation 4).

[0152]

number

[0153] In (Equation 4), the speed v, angle θ, and steering angle θ str is expressed as a function of time, but to determine whether or not the vehicle will come into contact with the obstacle Ob if it continues traveling as it is, the distance D calculated by the following (Equation 5) is used. pre may be used as the predicted distance.

[0154]

number

[0155] [Effects, etc.] The vehicle surroundings monitoring device 600 of the sixth embodiment further monitors the speed v and steering angle θ of the vehicle 5. str Based on the information on the above, the distance D between the vehicle 5 and the obstacle Ob after a predetermined time has elapsed is calculated. pre The distance prediction unit 606 predicts the distance.

[0156] According to this configuration, even if the vehicle 5 approaches the obstacle Ob and the obstacle Ob moves out of the detection range of the distance sensors 11 to 13, the distance of the vehicle 5 to the obstacle Ob can be predicted and contact with the obstacle Ob can be avoided.

[0157] (Embodiment 7) [composition] A description will be given of the configuration of a vehicle periphery monitoring device 700 according to embodiment 7. In embodiment 7, an example will be described in which the possibility of contact with an obstacle Ob is determined.

[0158] FIG. 20 is a block diagram showing a vehicle periphery monitoring system 1B including a vehicle periphery monitoring device 700 according to the seventh embodiment.

[0159] The vehicle periphery monitoring system 1B includes a plurality of distance sensors 11, 12, and 13, and a vehicle periphery monitoring device 700 that monitors the periphery of a vehicle 5. Each of the distance sensors 11 to 13 is the same as that in embodiment 1. The vehicle periphery monitoring system 1B also includes a speed sensor 50, a steering angle sensor 60, a warning display unit 70, a brake instruction unit 80, and a steering control unit 90.

[0160] The vehicle periphery monitoring device 700 according to the seventh embodiment includes a contact determination unit 707, a distance prediction unit 606, an angle derivation unit 505, a road surface determination unit 304, a normalization unit 203, an obstacle detection unit 201, and a memory 102. The distance prediction unit 606, the angle derivation unit 505, the road surface determination unit 304, the normalization unit 203, the obstacle detection unit 201, and the memory 102 are the same as those in the sixth embodiment.

[0161] The contact determination unit 707 determines the possibility of contact between the vehicle 5 and the obstacle Ob based on the distance between the vehicle 5 and the obstacle Ob. When the contact determination unit 707 determines that there is a possibility that the vehicle 5 will come into contact with the obstacle Ob, it outputs instructions to the warning display unit 70, the brake instruction unit 80, and the steering control unit 90 to avoid contact.

[0162] [Operation] The operation of the vehicle periphery monitoring device 700 according to the seventh embodiment will be described.

[0163] FIG. 21 is a flowchart showing the operation of the vehicle periphery monitoring device 700.

[0164] The contact determination unit 707 acquires the distances D2 and D3 from the vehicle 5 to the obstacle Ob detected by the obstacle detection unit 201 (step S710). pre is acquired (step S720).

[0165] The contact determination unit 707 determines these distances D2, D3 and D pre Based on this, the possibility of contact with the obstacle Ob is determined (step S730).

[0166] For example, the contact determination unit 707 determines the distances D2, D3, and D pre If any one of the distances is below the threshold distance at which the risk of contact increases, it is determined that there is a possibility of contact with the obstacle Ob (Yes in S730). In this case, the contact determination unit 707 outputs an instruction signal to the warning display unit 70, the brake instruction unit 80, and the steering control unit 90 to avoid contact (step S740).

[0167] Furthermore, the contact determination unit 707 determines the distances D2, D3, and D pre If all of the distances exceed the threshold distance, it is determined that there is no possibility of contact with the obstacle Ob (No in S730), and the flow shown in FIG. 21 ends.

[0168] [Effects, etc.] The vehicle periphery monitoring device 700 of the seventh embodiment further includes a contact determination unit 707 that determines the possibility of contact between the vehicle 5 and the obstacle Ob based on the distance between the vehicle 5 and the obstacle Ob.

[0169] According to this configuration, when the risk of contact with the obstacle Ob increases, it becomes possible to avoid contact with the obstacle Ob.

[0170] (Other embodiments) The above has described embodiments 1 to 7. However, the above embodiments are essentially preferred examples and are not intended to limit the scope of the present invention, its applications, or its uses.

[0171] For example, the distance sensors 11 to 13 may not be sensors dedicated to observing road surface conditions, but may be monitoring sensors that do not face the road surface. [Industrial Applicability]

[0172] The present disclosure can be widely used in fields such as automotive technology as a vehicle surroundings monitoring device that assists drivers in driving. [Explanation of symbols]

[0173] 1, 1A, 1B Vehicle Surroundings Monitoring System 5 vehicles 11, 12, 13 Distance sensors 50 Speed ​​Sensor 60 Steering angle sensor 70 Warning display section 80 Brake indicator 90 Steering control unit 100, 200, 300, 400, 500, 600, 700 Vehicle Surrounding Monitoring Device 101 Fault detection unit 102 memory 201 Fault detection unit 203 Normalization section 304 Road surface determination section 505 Angle Derivation Unit 606 Distance Prediction Unit 707 Contact determination section D2, D3, D mea , D pre distance L2 width dimension Obstacle R, R1, R2, R3 reflected waves TH obj Threshold W, W1, W2, W3 envelope θ angle

Claims

1. an obstacle detection unit that detects obstacles around the vehicle based on differences in envelopes of a plurality of reflected waves from a road around the vehicle, the differences being obtained by a plurality of distance sensors mounted on the vehicle; an envelope curve of each of the plurality of reflected waves is a curve on a coordinate system having a first axis representing time or distance and a second axis representing the intensity of the reflected wave, the curve including a first envelope curve and a second envelope curve different from the first envelope curve; Further, a normalization unit is provided that normalizes the second envelope curve based on the first envelope curve so as to reduce errors caused by differences in mounting conditions of the plurality of distance sensors. Vehicle surroundings monitoring device.

2. an obstacle detection unit that detects obstacles around the vehicle based on differences in envelopes of a plurality of reflected waves from a road around the vehicle, the differences being obtained by a plurality of distance sensors mounted on the vehicle; an envelope curve of each of the plurality of reflected waves is a curve on a coordinate system having a first axis representing time or distance and a second axis representing the intensity of the reflected wave, the curve including a first envelope curve and a second envelope curve different from the first envelope curve; Further, a road surface determination unit is provided that determines that the first envelope can be used as an envelope of a wave reflected from the road in front of or behind the vehicle when the first envelope is within a predetermined threshold range on the coordinate system. Vehicle surroundings monitoring device.

3. the first envelope is an envelope of a reflected wave from the road in front of or behind the vehicle, the reflected wave being obtained by a first distance sensor among the plurality of distance sensors; The second envelope is an envelope of a wave reflected from the road on the side of the vehicle, the envelope being obtained by a second distance sensor among the plurality of distance sensors.

3. The vehicle surroundings monitoring device according to claim 1 or 2.

4. The obstacle detection unit determines that the obstacle is present when a difference between the first envelope and the second envelope is greater than a predetermined threshold.

3. The vehicle surroundings monitoring device according to claim 1 or 2.

5. The obstacle detection unit derives a distance from the vehicle to the obstacle based on a difference curve that is a difference between the first envelope and the second envelope.

3. The vehicle surroundings monitoring device according to claim 1 or 2.

6. The obstacle detection unit derives a width dimension of the obstacle based on a difference curve that is a difference between the first envelope and the second envelope.

3. The vehicle surroundings monitoring device according to claim 1 or 2.

7. The road surface determination unit If the first envelope is within a predetermined threshold range on the coordinates, the first envelope is output as an envelope of a wave reflected from the road in front of or behind the vehicle and stored in a memory; If the first envelope is not within the predetermined threshold range, the past first envelope stored in the memory is output as an envelope of a wave reflected from the road in front of or behind the vehicle. The vehicle surroundings monitoring device according to claim 2.

8. The road surface determination unit If the entire first envelope is within a predetermined threshold range on the coordinates, output the first envelope as an envelope of a wave reflected from the road in front of or behind the vehicle; When a part of the first envelope is not within the range of the predetermined threshold, the envelope of the remaining part of the first envelope excluding the part is output as the envelope of the wave reflected from the road in front of or behind the vehicle. The vehicle surroundings monitoring device according to claim 2.

9. an obstacle detection unit that detects obstacles around the vehicle based on differences in envelopes of a plurality of reflected waves from a road around the vehicle, the differences being obtained by a plurality of distance sensors mounted on the vehicle; the envelopes of the plurality of reflected waves are curves on a coordinate system having a first axis representing time or distance and a second axis representing the intensity of the reflected waves, and include a first envelope, a second envelope different from the first envelope, and a third envelope different from the first envelope and the second envelope; the first envelope is an envelope of a reflected wave from the road in front of or behind the vehicle, the reflected wave being obtained by a first distance sensor among the plurality of distance sensors; the second envelope is an envelope of a wave reflected from the road on the side of the vehicle, the envelope being obtained by a second distance sensor among the plurality of distance sensors; the third envelope is an envelope of a wave reflected from the road on the side of the vehicle, the envelope being obtained by a third distance sensor among the plurality of distance sensors; further comprising an angle deriving unit that derives an angle of the traveling direction of the vehicle relative to the obstacle, The angle derivation unit derives an angle of the traveling direction of the vehicle based on the distance from the vehicle to the obstacle derived using the second envelope and the distance from the vehicle to the obstacle derived using the third envelope. Vehicle surroundings monitoring device.

10. The vehicle further includes a distance prediction unit that predicts the distance between the vehicle and the obstacle after a predetermined time has elapsed based on information about the speed and steering angle of the vehicle. The vehicle surroundings monitoring device according to claim 9.

11. The vehicle further includes a contact determination unit that determines the possibility of contact between the vehicle and the obstacle based on the distance between the vehicle and the obstacle. The vehicle surroundings monitoring device according to claim 10.

12. The distance sensor is an ultrasonic sensor, a radar, or a lidar.

3. The vehicle surroundings monitoring device according to claim 1 or 2.

13. 1. A vehicle surroundings monitoring method for detecting obstacles around a vehicle based on differences in envelopes of a plurality of reflected waves from a road around the vehicle, the reflected waves being obtained by a plurality of distance sensors mounted on the vehicle, the method comprising: an envelope curve of each of the plurality of reflected waves is a curve on a coordinate system having a first axis representing time or distance and a second axis representing the intensity of the reflected wave, the curve including a first envelope curve and a second envelope curve different from the first envelope curve; The second envelope is normalized based on the first envelope so that errors caused by differences in mounting conditions of the plurality of distance sensors are reduced. A method for monitoring the surroundings of a vehicle.

Images